CAJ | 학술논문

针对标准人工蜂群算法收敛速度慢和易陷入局部最优的缺点，提出一种基于混沌趋化行为的改进人工蜂群算法。在雇佣蜂和跟随蜂的搜索过程中引入细菌觅食优化算法的趋化思想，将随机产生蜜源的过程分解为翻转和前进两步，在翻转过程中引入混沌变量，提高算法的局部搜索能力。对5个典型测试函数的仿真结果表明，与标准人工蜂群算法相比，改进后的算法在收敛精度和速度方面均有明显提高。
침대표준인공봉군산법수렴속도만화역함입국부최우적결점，제출일충기우혼돈추화행위적개진인공봉군산법。재고용봉화근수봉적수색과정중인입세균멱식우화산법적추화사상，장수궤산생밀원적과정분해위번전화전진량보，재번전과정중인입혼돈변량，제고산법적국부수색능력。대5개전형측시함수적방진결과표명，여표준인공봉군산법상비，개진후적산법재수렴정도화속도방면균유명현제고。
To overcome the shortcomings of low convergence rate and easily sticking to local optimum of the basic artificial bee colony (ABC) algorithm ,an improved ABC algorithm based on the chaotic chemotaxis was proposed .The chemotaxis of bacteria foraging optimization algorithm was introduced into the search process of employed bees and onlooker bees . The randomly generating process of nectar sources was decomposed to two steps of turning and going ahead ,and the chaos variable was intro‐duced into the turning process .Thus the local search ability was improved .The simulation results based on five typical testing functions show that the improved ABC algorithm has better convergence precision and higher speed than the basic ABC algo‐rithm .